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GenAI has become an essential part of programming workflows, but most companies struggle to track its use, let alone it Return on investment. Israeli startup turn It hopes to help create a platform designed to link the use of AI tools to engineering metrics, including code quality.
The problem is that these companies must give Milestone access to their codebases, a bet that investors were initially skeptical of, CEO and co-founder Liad Elidan told TechCrunch. But with clients including Kayak, Monday and Sapiens, the startup has now raised a $10 million seed funding round led by San Francisco-based venture firm Heavybit and Israeli fund Hanaco Ventures.
In an unusual arrangement, Elidan and Milestone’s CTO had gone years without meeting in person by the time they started fundraising. Unlike most of the Milestone team members who are based in Israel, Professor Stephen Barrett lives in Ireland and teaches computer science at Trinity College Dublin, where Illidan was once his student and the two bonded over software projects.
Despite the distance, the duo kept in touch over the years, eventually deciding to found a startup focused on engineering efficiency, just as programming assistants and other code generation tools were starting to take off. GitHub Copilot since then It has exceeded 20 million usersbut companies still lack visibility into how these tools are used and their impact on productivity.
According to Illidan, Milestone answers these questions by relying on four pillars — codebases, project management platforms, team structure, and the code generation tools themselves — to create what he describes as a “genetic AI data lake.” In practical terms, this provides organizations with actionable data about which teams are using AI and to what effect – thanks to their proprietary information.
Armed with this data, managers, who are under constant pressure to leverage AI to increase productivity, are able, for example, to measure the speed of feature delivery, but also to see if recent bugs are caused by AI-generated code, and make informed decisions about where to implement these tools, Illidan said.
This also gives Milestone a front-row seat to ROI – the “supreme question” it aims to answer in detail for its clients. But at a high level, he said, “We don’t have a customer who has used Milestone and said, ‘Well, GenAI isn’t helping me, I’m going to revoke all my licenses.’ It’s actually the opposite. They want to try more general AI tools.”
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This rapid adoption also means that Milestone has to keep up with the rapidly evolving landscape. “It was autocomplete, then it was chat, then it was agent-based chat, and it keeps going,” Illidan said.
This is also where Barrett’s academic background helps the team understand the wave of transformation its clients are experiencing. “A lot of the ways we used to think about engineering have to change,” the professor told TechCrunch. “I think, to some extent, AI is filling the team, and engineers are now managers.”
To keep up with the tools powering this wave, Milestone says it has partnered with several vendors, such as GitHub, Augment Code, Qodo, Continue, and Atlassian — the company that powers Jira and whose venture arm Atlassian Ventures also participated in this seed round.
The round was also backed by angel investors, including GitHub co-founder Tom Preston-Werner, former AT&T CEO John Donovan, Accenture chief technology advisor Paul Dougherty, and former Datadog chief Amit Agrawal — who all recognize that what Milestone is building is right for the enterprise market, Illidan said.
This enterprise focus was intentional from day one, and Milestone even said no to potential clients who were very small — “It’s a very difficult thing to do,” Illidan said — but it gave the startup clarity around a roadmap that required enterprise credentials and features. Focus would be his main advice to other founders, and Milestone takes it: The startup won’t expand on measuring GenAI’s impact on marketing or other functions, even as it grows.